David Heckerman
- Virology top 0.2%
- HIV Research and Treatment 64
- Artificial Intelligence top 0.05%
- Bayesian Modeling and Causal Inference 62
- AI-based Problem Solving and Planning 19
- Machine Learning and Algorithms 15
- Signal Processing top 0.5%
- Information Systems top 0.1%
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- vaccines and immunoinformatics approaches 37
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- Immune Cell Function and Interaction 26
- T-cell and B-cell Immunology 24
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- HIV/AIDS drug development and treatment 14
- Co-authors
- Dan GeigerDavid M. ChickeringEric HorvitzMehran SahamiSusan DumaisCarl KadieJennifer ListgartenJohn Platt
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
David Heckerman
211 papers receiving 16.8k citations
Hit Papers
Peers
Comparison fields: 5 of 213
- Virology 2.6k
- Artificial Intelligence 7.9k
- Signal Processing 1.4k
- Information Systems 2.6k
- Management Science and Operations Research 1.4k
Countries citing papers authored by David Heckerman
This map shows the geographic impact of David Heckerman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Heckerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Heckerman more than expected).
Fields of papers citing papers by David Heckerman
This network shows the impact of papers produced by David Heckerman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Heckerman. The network helps show where David Heckerman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Heckerman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 52 | |
| 2 | 2012 | 44 | |
| 3 | 2011 | 77 | |
| 4 | 2011 | 13 | |
| 5 | 2011 | 45 | |
| 6 | 2010 | 61 | |
| 7 | 2007 | 52 | |
| 8 | 2006 | 84 | |
| 9 | Recommendation as a stochastic sequential decision problem | 2003 | 9 |
| 10 | The Learning Curve Method Applied to Clustering | 2001 | 2 |
| 11 | Learning mixtures of smooth, nonuniform deformation models for probabilistic image matching. | 2001 | 1 |
| 12 | A Bayesian Approach to Filtering Junk E-Mailbreakdown → | 1998 | 769 |
| 13 | A characterization of the bivariate wishart distribution | 1998 | 7 |
| 14 | Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining | 1997 | 204 |
| 15 | Challenge: what is the impact of Bayesian networks on learning? | 1997 | 16 |
| 16 | A combination of cutset conditioning with clique-tree propagation in the Pathfinder system | 1990 | 14 |
| 17 | A Probabilistic Reformulation of the Quick Medical Reference System | 1990 | 7 |
| 18 | 1987 | 46 | |
| 19 | The role of calculi in uncertain reasoning | 1987 | 6 |
| 20 | A Bayesian Perspective on Confidence. | 1987 | 8 |
About David Heckerman
David Heckerman is a scholar working on Virology, Artificial Intelligence and Immunology, having authored 219 papers that have together received 18.1k indexed citations. Recurring topics across this work include HIV Research and Treatment (64 papers), Bayesian Modeling and Causal Inference (62 papers), vaccines and immunoinformatics approaches (37 papers), Immune Cell Function and Interaction (26 papers), T-cell and B-cell Immunology (24 papers), AI-based Problem Solving and Planning (19 papers), Machine Learning and Algorithms (15 papers) and HIV/AIDS drug development and treatment (14 papers). The work is most often cited by research in Virology (2.6k citations), Artificial Intelligence (7.9k citations) and Signal Processing (1.4k citations). David Heckerman has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Dan Geiger, David M. Chickering, Eric Horvitz, Mehran Sahami, Susan Dumais, Carl Kadie, Jennifer Listgarten, John Platt, Christoph Lippert and David Maxwell Chickering. Their work appears in journals such as Journal of Virology, PLoS ONE, Machine Learning, Bioinformatics and PLoS Computational Biology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.